All B5 Publications

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  • Salim, M. H., Schlünzen, H., Grawe, D., Boettcher, M., Gierisch, A. M. U., & Fock, B. (2018). The microscale obstacle-resolving meteorological model MITRAS v2.0: model theory. Geoscientific Model Development, 11(8), 3427-3445. doi:10.5194/gmd-11-3427-2018.
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  • Fischereit, J., & Schluenzen, K. H. (2018). Evaluation of thermal indices for their applicability in obstacle-resolving meteorology models. International Journal of Biometeorology, 62, 1887-1900. doi:10.1007/s00484-018-1591-6.
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  • Karki, R., Hasson, S., Gerlitz, L., Talchabhadel, R., Schenk, E., Schickhoff, U., Scholten, T., & Böhner, J. (2018). WRF-based simulation of an extreme precipitation event over the Central Himalayas: Atmospheric mechanisms and their representation by microphysics parameterization schemes. Atmospheric Research, 214, 21-35. doi:10.1016/j.atmosres.2018.07.016.
  • Dehghani Pour, M., Barati, A. A., Azadi, H., & Scheffran, J. (2018). Revealing the role of livelihood assets in livelihood strategies: Towards enhancing conservation and livelihood development in the Hara Biosphere Reserve, Iran. Ecological Indicators, 94(part 1), 336-347. doi:10.1016/j.ecolind.2018.05.074.
  • Bobrowski, M., Bechtel, B., Böhner, J., Oldeland, J., Weidinger, J., & Schickhoff, U. (2018). Application of Thermal and Phenological Land Surface Parameters for Improving Ecological Niche Models of Betula utilis in the Himalayan Region. Remote Sensing, 10(6): 814, pp. 1-19. doi:10.3390/rs10060814.
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  • Zou, Z., Zhan, W., Liu, Z., Bechtel, B., Gao, L., Hong, F., Huang, F., & Lai, J. (2018). Enhanced Modeling of Annual Temperature Cycles with Temporally Discrete Remotely Sensed Thermal Observations. Remote Sensing, 10(4): 650, pp. 1-12. doi:10.3390/rs10040650.
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  • Yang, L., Scheffran, J., Hoffmann, P., Rühe, S., Fischereit, J., & Gasser, I. (2018). An Agent-Based Modeling Framework for Simulating Human Exposure to Environmental Stresses in Urban Areas. Urban Science, 2(36), 1-21. doi:10.3390/urbansci2020036.
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  • Bechtel, B., & Sismanidis, P. (2018). Time series analysis of moderate resolution land surface temperatures. In Q. Weng (Ed.), Remote Sensing: Time Series Image Processing. Taylor & Francis.
  • Bechtel, B., Pesaresi, M., Florczyk, A. J., & Mills, G. (2018). Beyond built-up – the internal makeup of urban areas. In Q. Weng, D. Quattrochi, & P. E. Gamba (Eds.), Urban Remote Sensing (2nd. ed.). Boca Raton: CRC Press.
  • Wiesner, S., Bechtel, B., Fischereit, J., Grützun, V., Hoffmann, P., Leitl, B., Rechid, D., Schlünzen, H., & Thomsen, S. (2018). Is It Possible to Distinguish Global and Regional Climate Change from Urban Land Cover Induced Signals? A Mid-Latitude City Example. Urban Science, 2(1): 12, pp. 1-22. doi:10.3390/urbansci2010012.
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Related Publications (CliSAP 1, 2007-2012)

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  • Bechtel, B. (2012). Classification of Local Climate Zones from multitemporal remote sensing data. Urban Climate News, 46, 7-14.
  • Wiesner, S., Eschenbach, A., & Ament, F. (2012). Erfassung des Einflusses von Feuchte- und Energieflüssen städtischer Böden auf das lokale Klima. In Tagungsband zur 31. Sitzung des Arbeitskreis Klima.
  • Schlünzen, H. (2012). Stadtklima: Wärmeinseln im Treibhaus. Spektrum der Wissenschaft - Extra, http://www.spektrum.de/artikel/1142728.
  • Sandoval, S., Eschenbach, A., & Ament, F. (2012). Erfassung des Einflusses von Feuchte- und Energieflüssen städtischer Böden auf das lokale Klima. In Wissenschaftliche Mitteilungen aus dem Institut für Meteorologie der Universität Leipzig, 49: METTOOLS VIII Tagungsband (pp. 129).
  • Sandoval, S., Ament, F., & Eschenbach, A. (2011). Observing moisture and energy exchange of urban soils and the impact on local climate. Geophysical Research Abstracts, 13, EGU2011-7819.
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  • Tomassini, L., Hagemann, S., Moseley, C., Haumann, A., Podzun, R., & Jacob, D. (2011). Extremes and predictability in the European pre-industrial climate of a regional climate model. Climate Dynamics, 36, 2371-2397. doi:10.1007/s00382-010-0814-2.
  • Sandoval, S., Ament, F., & Eschenbach, A. (2010). Hamburg Urban Soil Climate Observatory (HUSCO): A concept to assess the impact of moisture and energy fluxes of urban soils on local climate. Geophysical Research Abstracts, 12, EGU2010-4265.
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